NON-DESTRUCTIVE LEAK DETECTION IN GALVANIZED IRON PIPE USING NONLINEAR ACOUSTIC MODULATION METHOD

Non-destructive testing is a wide group of analysis techniques used in science and industry to evaluate the properties of a structure without causing damage to it. The main objective of this project is to carry out experiment to detect leakage in pipeline using nonlinear acoustic modulation method. The nonlinear acoustic modulation approach with low frequency excitation and high frequency acoustic wave is used to reveal modulations in the presence of leak. The pipe used in this experiment was galvanized iron pipe. The experiment is started with the experiment of undamaged specimen and followed by the experiment of damaged specimen with manually applied leak. The results obtained are being observed and the difference between the specimen without leak and with leak can be distinguished. The distance of the leak and the distance of the outlet detected is nearly accurate to the exact location which is leak at 4.0 m and outlet at 6.0 m. Therefore, the results demonstrate that leakage can be detected using nonlinear acoustic modulation, and proved the objective of distinguish the difference between the results of specimen without leak and with leak has succeeded. The damage detection process can be eased with the knowledge on the signal features

Análisis aerodinámico de un vehículo aéreo no tripulado con forma de halcón para monitoreo de fugas de hidrocarburos

The oil pipeline network requires periodic monitoring to detect pipeline damages, which may cause oil leakage with severe environmental contamination. These damages can be generated by interference from third parties such as construction works, sabotage, vandalism, excavations, and illegal oil theft. To detect the oil pipeline damages, it can be used aerodynamic aerial vehicles (UAVs) with infrared cameras and image processing systems. This paper presents the aerodynamic analysis of a UAV with a hawk shape (wingspan of 2.20 m and length of 1.49 m) for potential application in the detection of oil pipeline failures. A 1:6.5 scale prototype of the UAV is fabricated using a 3D printer. The aerodynamic coefficients of UAV are determined using computational fluid dynamic (CFD) simulations and experimental testing with a subsonic wind tunnel. In addition, the lift and drag coefficients of UAVs are obtained as a function of Reynolds number and angle of attack. Also, the air velocity profile around UAV is estimated with the CFD model. The proposed UAV could decrease the inspection costs of pipeline networks in comparison with the use of helicopters or light aircraft.La red de oleoductos requiere monitoreo periódico para detectar daños que puedan causar fugas de hidrocarburos con severo daño ambiental. Estos daños pueden generarse por interferencia de terceros, tales como trabajos de construcción, sabotaje, vandalismo, excavaciones y sustracción ilegal de hidrocarburos. Para detectar daños en oleoductos pueden utilizarse vehículos aéreos no tripulados (UAVs) con cámaras infrarrojas y sistemas de procesamiento de imágenes. Este trabajo presenta el análisis aerodinámico de un UAV con forma de halcón (envergadura de 2,20 m y longitud de 1,49 m) para aplicación potencial en la detección de fallas de oleoductos. Un prototipo a escala de 1:6,5 es fabricado usando una impresora 3D. Los coeficientes aerodinámicos del UAV son determinados usando simulaciones de dinámica de fluidos computacionales (CFD) y pruebas experimentales con un túnel de viento subsónico. Además, los coeficientes de sustentación y arrastre del UAV son obtenidos como función del número de Reynolds y el ángulo de ataque. También, el perfil de velocidad del aire alrededor del UAV es estimado con el modelo CFD. El UAV propuesto podría disminuir los costos de inspección de oleoductos en comparación con el uso de helicópteros o vehículos aéreos ligeros

Framework for integrated oil pipeline monitoring and incident mitigation systems

Wireless Sensor Nodes (motes) have witnessed rapid development in the last two decades. Though the design considerations for Wireless Sensor Networks (WSNs) have been widely discussed in the literature, limited investigation has been done for their application in pipeline surveillance. Given the increasing number of pipeline incidents across the globe, there is an urgent need for innovative and effective solutions for deterring the incessant pipeline incidents and attacks. WSN pose as a suitable candidate for such solutions, since they can be used to measure, detect and provide actionable information on pipeline physical characteristics such as temperature, pressure, video, oil and gas motion and environmental parameters. This paper presents specifications of motes for pipeline surveillance based on integrated systems architecture. The proposed architecture utilizes a Multi-Agent System (MAS) for the realization of an Integrated Oil Pipeline Monitoring and Incident Mitigation System (IOPMIMS) that can effectively monitor and provide actionable information for pipelines. The requirements and components of motes, different threats to pipelines and ways of detecting such threats presented in this paper will enable better deployment of pipeline surveillance systems for incident mitigation. It was identified that the shortcomings of the existing wireless sensor nodes as regards their application to pipeline surveillance are not effective for surveillance systems. The resulting specifications provide a framework for designing a cost-effective system, cognizant of the design considerations for wireless sensor motes used in pipeline surveillance

Dynamic reliability model for subsea pipeline risk assessment due to third-party interference

This research was sponsored by the Ministry of Finance of the Republic of Indonesia through the Indonesia Endowment Fund for Education (LPDP RI) (grant number: PRJ-4202 /LPDP.3/2016).Peer reviewedPublisher PD

Large Occupational Accidents Data Analysis with a Coupled Unsupervised Algorithm: The S.O.M. K-Means Method. An Application to the Wood Industry

Data on occupational accidents are usually stored in large databases by worker compensation authorities, and by the safety and prevention teams of companies. An analysis of these databases can play an important role in the prevention of accidents and the reduction of risks, but it can be a complex procedure because of the dimensions and complexity of such databases. The SKM (SOM K-Means) method, a two-level clustering system, made up of SOM (Self Organizing Map) and K-Means clustering, has obtained positive results in identifying the dynamics of critical accidents by referring to a database of 1200 occupational accidents that had occurred in the wood industry. The present research has been conducted to validate the recently presented SKM methodology through the analysis of a larger data set of more than 4000 occupational accidents that occurred in Piedmont (Italy), between 2006 and 2013. This work has partitioned the accidents into groups of different accident dynamics families and has quantified the severity and frequency of occurrence of these accidents. The obtained information may be of help to Company Managers and National Authorities to better address preventive measures and policies concerning the clusters that have been identified as being the most critical within a risk-based decision-making framework

Risk Analysis of Natural Gas Distribution Pipelines with Respect to Third Party Damage

The objective of this study is to develop a quantitative method of evaluating the risk of third party damage (TPD) on natural gas distribution pipelines using available industry data and practical engineering experience. A risk model for TPD of gas distribution pipelines is developed to allow for a more robust decision making process and better prioritization of the allocation of resources for operators of natural gas distribution pipelines. The model consists of likelihood and consequence classification procedures to estimate the severity of TPD events within an area. The TPD model consists of a fault tree (FTA) model to estimate the probability of hit of a given distribution pipeline by third party excavation activities. The distribution FTA model is developed using TPD and locate records from 2014-2016 and survey data from transmission FTA models. This model is then validated by comparing the predicted and actual 2017 damage records in three municipalities in southwestern Ontario with populations varying from 200,000 to 350,000. Based on a historical analysis of distribution pipeline TPD consequence, a procedure is developed to classify the consequence of a TPD event within a given area. Methods of collecting and classifying data from sources available to distribution companies are used to allow this procedure to be implemented straightforwardly in an industry setting. In a case study a compromise solution method of evaluation is used to identify areas where focusing damage prevention resource would be most effective

Risk Assessment of Pipeline on Third-Party Damage in Oil and Gas Industry with Bayesian Network and Game Theory

Tremendous amount of oil and gas products are transported in pipeline worldwide giving rise to a demand to identify the hazards and evaluate the associated risk. Third-party intrusion is usually one of the least factors being considered during the pipeline hazard assessment stage despite the substantial portion contributing to the total number of oil and gas pipeline incident. This is because of the probabilistic risk assessment defect that makes it hard to model human actions and cannot be applied to intentional acts. Due to the distinctive motivations of third-party damage, an unintentional third-party damage Bayesian Network model and a game-theoretic model on malicious intrusion will therefore be built, respectively to examine the mechanism of pipeline failure caused by this mode. This study is conducted aiming at investigating pipeline risk resulting from third-party damage, and will formulate risk assessment models to identify threats, prioritize risks and determine which integrity plan should apply to different pipeline segments given the condition of third-party interference (both the accidental damage and malicious acts). In other words, it can help to anticipate an optimal planning of the in-line inspection intervals which can decrease the risk of the pipeline to an acceptable level and achieve cost-effective pipeline integrity management